Update app.py

app.py

@@ -32,6 +32,17 @@ def remove_html_tags(text):
 
 df['content'] = df.content.apply(lambda x: remove_html_tags(x))
 df['summary_html'] = df.summary_html.apply(lambda x: remove_html_tags(x))
+#testing new code
+session_prompt = """ A bot that is open to discussions about different cultural, philosophical and political exchanges. I will use do different analysis to the articles provided to me. Stay truthful and if you weren't provided any resources give your oppinion only."""
+
+def new_ask(user_input):
+  response = openai.ChatCompletion.create(model ="gpt-3.5-turbo",
+                               messages = [{'role': 'system', 'content': session_prompt},{'role': 'user', 'content': user_input}],
+                               temperature = 0
+
+  )
+  # print(response)
+  return response['choices'][0]['message']['content']
 
 def search(query):
     n = 10
@@ -43,19 +54,46 @@ def search(query):
     #results = results[['title','url','keywords','summary_html']].drop_duplicates()  
     results = r_groupby.reset_index()
     results = results.sort_values("similarity", ascending=False)
-    resultlist = []
+    tier_1 = []
+    tier_2 = []
     for r in results.index:
-        resultlist.append(
-            {
-              "Title":results.title[r],
-                "url":results.url[r],
-             "score": str(results.similarity[r][0]),
-             "summary": results.summary_html[r][:200],
-                "keywords": results.keywords[r]
-            }
-        )
-        
-    return resultlist
+
+        if results.similarity[r][0] > 0.5:
+
+          tier_1.append(
+              {
+                "title":results.title[r],
+                  "url":results.url[r],
+              "score": str(results.similarity[r][0]),
+              "summary": results.summary_html[r][:200],
+                  "keywords": results.keywords[r]
+              }
+          )
+
+        elif results.similarity[r][0] > 0.4:
+          tier_2.append(
+              {
+                "title":results.title[r],
+                  "url":results.url[r],
+              "score": str(results.similarity[r][0]),
+              "summary": results.summary_html[r][:200],
+                  "keywords": results.keywords[r]
+              }
+          )
+    print(tier_1)
+    print(tier_2)
+    ln = "\n"
+    prefix = f"tier 1:\n{ln.join([x['title'] for x in tier_1])}"
+    print(prefix)
+    answer = new_ask(f"Answer the following query by giving arguments from the different arguments provided below. Make sure to quote the article used if the argument corrseponds to the query: Query: {query} Articles {ln.join([x['title'] + ': ' + x['summary'] for i, x in enumerate(tier_1)])}\nUse careful reasoning to explain your answer and give your conclusion about this.")
+    
+    if len(tier_2):
+      suffix = f"tier 2:\n{ln.join([x['title'] for x in tier_2])}"
+      related_questions = new_ask(f"Give general questions related the following articles: {ln.join([str(i) + ' ' + x['summary'] for i, x in enumerate(tier_2)])}")
+      
+      return f"{answer}\n\nRelated Questions:\n{related_questions}"
+    
+    return f"{answer}"
 
 def greet(query):
    
@@ -66,14 +104,10 @@ examples = [
     ["Climate Change Challenges in Europe"],
     ["Philosophy in the world of Minimalism"],
     ["Hate Speech  vs Freedom of Speech"],
-    ["Articles by Noam Chomsky on US Politics"],
     ["The importance of values and reflection"]
     ]
 
-demo = gr.Interface(fn=greet, title="cicero-semantic-search", 
-                     inputs=gr.inputs.Textbox(lines=5, label="what would you like to learn about?"),
-                     outputs="json",examples=examples)
-
-demo.launch()
-
+demo = gr.Interface(fn=greet, title="cicero-interactive-qa", 
+                     outputs = "text",inputs=gr.inputs.Textbox(lines=5, label="what would you like to learn about?"),examples=examples)
 
+demo.launch(share = True, debug = True)